The targeted treatment of weeds is an expanding part of precision farming in many countries. Targeted weed treatments, using precision spray maps, reduce herbicide consumption, whilst still maintaining long term weed control. Assembling accurate spray maps is a vital part of this process. However, acceptable accuracy in spray maps is difficult to quantify, due in part to rapid technological advances in cameras, weed recognition software, and herbicide decision support systems (DSS). This research applied a DSS to repeated samples from field gathered weed data. Variability in the herbicide recommendations when different numbers of images were used for the same areas (polygons) within a field were examined. Type 2 errors (not recommending herbicide where it was needed), were analysed separately to type 1 errors (recommending herbicide where it was not needed). Type 2 errors were more common than type 1 errors in diagnosing herbicides to control Viola arvensis in Field 1, and Poaceae species in Field 2, and were also more common with systematically dispersed images compared to randomly dispersed images. In contrast, type 2 errors were less common than type 1 errors for Poaceae species in Field 1. Variability in herbicide recommendations differed for herbicides but was generally reduced (1) with greater numbers of images per polygon; (2) by using regularly arranged images; and (3) for datasets with greater ratios of ‘empty’ (not needing spray) polygons. Targeted treatments reduced herbicide use to 3–11% of the rate recommended for blanket spraying of the same weeds. High numbers of ‘empty’ polygons gave better results with lower relative percentages of type 1 errors. These results highlight the need to focus on reducing type 2 errors in spatial herbicide recommendations.

在许多国家，对杂草的有针对性处理已成为精准农业的一个扩展部分。使用精确的喷雾图进行有针对性的杂草处理，可减少除草剂的消耗，同时仍能长期控制杂草。组装准确的喷雾图是此过程的重要组成部分。但是，由于地图，杂草识别软件和除草剂决策支持系统（DSS）的快速技术进步，喷雾地图中可接受的精度难以量化。这项研究将DSS应用于野外采集的杂草数据的重复样本中。检查了在田间相同区域（多边形）使用不同数量的图像时除草剂建议的可变性。第2类错误（不建议在需要的地方使用除草剂），分别分析了1类错误（建议在不需要的地方使用除草剂）。诊断除草剂以控制时，2型错误比1型错误更常见。中提琴与随机分散的图像相比，在系统分散的图像中，字段1中的禾本科物种和字段2中的禾本科物种更为常见。相反，在田野1中，禾本科物种的2型错误比1型错误更不常见。除草剂建议的变异性对于除草剂有所不同，但通常会降低（1），每个多边形的图像数量更多；（2）使用规则排列的图像；（3）对于“空”（不需要喷涂）多边形比例更大的数据集。有针对性的处理将除草剂的使用量减少到建议对相同杂草进行全面喷洒的比例的3–11％。大量的“空”多边形给出了更好的结果，而类型1错误的相对百分比更低。这些结果凸显了在减少空间除草剂建议中需要重点减少2型错误的必要性。